# Modeling competitive evolution of multiple languages

## TL;DR

This paper extends a language competition model to multiple languages, analyzing data from Singapore and Hong Kong to understand how biases influence language coexistence, decline, or extinction, and identifying critical tipping points affecting language dynamics.

## Contribution

The study develops a multi-language extension of the Abrams-Strogatz model and validates it with real-world data, revealing how biases impact language evolution and stability.

## Key findings

- Biases determine the fastest-growing language and stable states.
- Tipping points lead to multiple attractors and critical slowdown.
- Understanding these dynamics can help protect language diversity.

## Abstract

Increasing evidence demonstrates that in many places language coexistence has become ubiquitous and essential for supporting language and cultural diversity and associated with its financial and economic benefits. The competitive evolution among multiple languages determines the evolution outcome, either coexistence, decline, or extinction. Here, we extend the Abrams-Strogatz model of language competition to multiple languages and then validate it by analyzing the behavioral transitions of language usage over the recent several decades in Singapore and Hong Kong. In each case, we estimate from data the model parameters that measure each language utility for its speakers and the strength of two biases, the majority preference for their language, and the minority aversion to it. The values of these two biases decide which language is the fastest growing in the competition and what would be the stable state of the system. We also study the system convergence time to stable states and discover the existence of tipping points with multiple attractors. Moreover, the critical slowdown of convergence to the stable fractions of language users appears near and peaks at the tipping points, signaling when the system approaches them. Our analysis furthers our understanding of multiple language evolution and the role of tipping points in behavioral transitions. These insights may help to protect languages from extinction and retain the language and cultural diversity.